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TRUTH AND THE SCIENCES

Anjan Chakravartty Institute for the History and Philosophy of Science and Technology, and Department of Philosophy

University of Toronto Abstract. Conceptions of truth in relation to the sciences vary extensively along two dimensions. The first concerns the applicability of the notion of truth to scientific knowledge, resulting in a number of contentions: that scientific knowledge is wholly, or in some important sense, independent of truth; that truth is, in some form, a proper aim of science; and that truths are, in fact, illuminated by means of scientific investigation. The second dimension concerns the particular theory of truth one might think applicable, and here one finds a variety of preferences, including: truth as coherence, especially suited to historicist and sociological approaches to science; truth as utility, described by pragmatist approaches to science; and truth via correspondence or truth-‐making, especially in the context of various forms of “realism” in connection with scientific knowledge. In this essay, I travel along the first dimension in the direction of increasing commitment to the applicability of truth, and in each case explore the second dimension: how different views of scientific knowledge appeal, explicitly or implicitly, to different theories of truth.

1. Introduction

What is the relationship of truth to the sciences? Ideally, as a prelude to answering this

question, one might begin by specifying what, in this context, truth is generally thought to be.

Unfortunately, however, though many philosophers of science believe that the concept of truth is

important to a consideration of the practice and outcomes of scientific work, there is no consensus

regarding which concept of truth, among the several philosophers have developed more generally,

is most appropriate here. Indeed, there is no consensus even regarding the question of whether the

concept is relevant to philosophical considerations of the sciences, and if so, how. In light of this

diversity of opinion, perhaps not surprisingly, the task of getting to grips with the relationship of

truth to the sciences is not entirely straightforward: it requires an examination of the different

approaches to scientific investigation and knowledge that generate these different commitments. In

this essay, I explore the many different ways in which concepts of truth have been brought to bear

in connection with these different approaches.

The various attitudes towards truth found in the philosophy of science have correlates in a

number of what one might view as philosophically pre-‐reflective attitudes exemplified in everyday

discussions and debates about science. The different philosophical approaches towards the

sciences I have alluded to may thus be thought of as more careful or rigorous philosophical

extensions of these everyday attitudes. By way of introduction, then, it may be helpful to enumerate

these pre-‐reflective attitudes before digging into their philosophical counterparts. On the one hand,

Anjan Chakravartty Truth and the Sciences

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there are more or less “optimistic” attitudes regarding the connection between truth and the

sciences – those that view the sciences as producing truths concerning the natural and social

worlds in which we live, or as arbiters with respect to such truths, or at the very least, our best bets

for truth production and arbitration. On the other hand, there are more or less “pessimistic”

attitudes, which regard the connection as relatively weak or in some cases, illusory. Let us consider

this range of possibilities, briefly, in turn.

Almost everyone, I suspect, would agree that the sciences are in the knowledge production

business – scientific work produces theories, models, predictions, and explanations which are

offered, prima facie, as candidates for knowledge. The optimism and pessimism I have gestured

towards concern the extent to which these candidates can or should be thought of in terms of truth.

Optimists commonly hold that our best scientific theories and models can be thought of as yielding

truths regarding their subject matter, or as furnishing descriptions that are, over time, approaching

the truth (in a sense to be specified, as we shall see in sections 3 and 5). This is the implicit attitude

exemplified in everyday contexts in which scientists are presented as authorities regarding

everything from the common cold to genetic manipulation to climate change. This generally

positive view of the connection between science and truth has its most pronounced philosophical

extension in varieties of “realism” with respect to scientific knowledge. Realists of different sorts

typically defend the proposition that our best scientific theories provide true or approximately true

descriptions of the world, but in different ways: some defend realism rather generally, and others

only with respect to certain classes of ontological or other claims which they assess as having

greater epistemic warrant than others.

One need not be a realist, however, in order to adopt a positive attitude towards the

connection between science and truth. A certain degree of pessimism with respect to truth is

compatible with a degree of optimism. There are those, for example, who are somewhat suspicious

of the often definitive-‐ and precise-‐sounding claims of scientists – particularly in connection with

things very far removed from our abilities to see or otherwise register information in the absence of

elaborate instrumentation. Examples of such things may include the very small, such as viruses and

subatomic particles, or the very spatiotemporally distant, such as events in the immediate

aftermath of the Big Bang or those leading to the extinction of the dinosaurs. Some sceptics

nevertheless hold that scientists are likely on to something, even if they are suspicious about their

furthest reaching claims. This everyday attitude also has well developed philosophical extensions. A

number of philosophical positions, including certain varieties of empiricism, regard the sciences as


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producing truths, but of a restricted subset of scientific claims comprising descriptions of

observable phenomena (as opposed to other, less directly detectable phenomena).

Of course, it is possible to be even more strongly sceptical. One might doubt that the

sciences produce truths at all, or that while they might do so on occasion, there is little reason to

think that they are particularly successful in this regard. Everyday scepticism about the veracity of

scientific knowledge has its source in a multiplicity of motivations, from the epistemological to the

religious, social, and political. In the philosophy of science, the motivations for this stronger

sceptical attitude are invariably epistemological, but in some cases these views do have important

social and political dimensions. Some who ascribe to strongly historicist conceptions of knowledge

doubt that truth is especially relevant to an assessment or understanding of scientific knowledge.

Social constructivist and feminist critiques of the notion of truth and associated concepts, such as

objectivity, engage head-‐on with the socio-‐political implications of these ideas, thereby injecting a

consideration of them into the epistemology of science.

In what follows, I will outline the range of views that have emerged in the philosophy of

science regarding the notion of truth. I will begin in section 2 with views that ascribe no role, or a

limited role, to truth in connection with scientific practice and knowledge. The primary driver of

scepticism about the role of truth here is most commonly manifested as a dissatisfaction with the

correspondence theory of truth, according to which truth is a matter of corresponding, in the right

sort of way, to a mind-‐independent reality. (The correspondence theory holds that a belief

(statement, proposition, etc.) is true if it corresponds to the way this reality is, or to the facts or

states of affairs that make it up; for a detailed treatment of the view in this volume, see David.) In

some of these cases, an account of truth in terms of coherence – that is, in terms of the consistency

of a set of beliefs (statements, propositions, etc.) – may better accord with the relevant approaches

to science. (The coherence theory holds that a belief is true if it is part of a coherent system of

beliefs; on this view, see Walker.) In section 3, I will examine positions that view truth in some form

as an appropriate aim of science, and in section 4, I will consider the even stronger commitment to

truth adopted by positions that regard it not merely as an aim, but as an achievement of scientific

investigation. In the latter case, truth is generally conceived in terms of some sort of

correspondence, or truth-‐making, or both.

One may think of considerations of truth in connection with the sciences by means of two

analytical dimensions: the first concerning the degree to which one may think the notion is

applicable to the sciences; and the second concerning the precise theory of truth one may think

applies. I will consider, in turn, views that are increasingly interested in truth, and for each, identify


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the theory or theories of truth that are most appropriate. In section 5, I will conclude with an

overview of some challenges regarding truth to emerge in recent work, particularly in connection

with scientific realism, the most truth-‐indulgent philosophy of science.

2. Truth as Orthogonal to Scientific Knowledge

2.1 Historicism and practice-‐oriented philosophy of science

Logical positivism (or logical empiricism), the founding movement of the philosophy of

science as a recognizably distinct sub-‐discipline of philosophy, dominated the field for much of the

twentieth century. In the 1960s, the demise of positivism was hastened by a historical turn in the

philosophy of science, associated with authors such as Thomas Kuhn, Paul Feyerabend, and

Norwood Russell Hanson, which set the stage for many of the issues discussed in the philosophy of

science to this day. In particular, Kuhn’s extraordinarily influential book, The Structure of Scientific

Revolutions, played a large role in establishing a form of historicism about scientific knowledge, and

an allied (though strictly separable) preoccupation with the actual practice of science by scientists,

both of which have significant consequences for thinking about truth. I will take Kuhn’s views as

exemplary in this regard for present purposes, though it is important to note that in a number of

respects, the morals I will draw concerning truth apply in partially overlapping ways to some of his

positivist ancestors, and most certainly to a number of his contemporaries.

The underlying commitment of the approach to science taken in the historical turn was to

treat the history of the sciences and their constituent practices seriously as a means by which to

investigate the nature of scientific knowledge. This was a self-‐conscious attempt at descriptive

philosophy – describing the nature of scientific knowledge as it is actually found – as opposed to a

normative or more abstract exercise in idealized epistemological speculation. Kuhn presented the

history of the sciences as displaying a recurring pattern of development: periods of so-‐called

normal science punctuated by scientific revolutions, which overturned the established order and

thereby laid the foundations for a new period of normal science. One might regard classical physics,

for example, as spanning a period of normal science, which was ultimately replaced by relativistic

and quantum physics, which in part constitute the normal science of our own time. The key

implications for truth on this picture derive from Kuhn’s characterization of knowledge on either

side of a revolutionary divide. Two different periods of normal science, he held, are


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incommensurable with one another, and indeed, exemplify a phenomenon that is now commonly

referred to as world change. Let us consider these ideas, briefly, in turn.1

Kuhn held that each period of normal science is typified by a shared commitment to a

‘disciplinary matrix’ or ‘paradigm’, consisting of a number of elements: symbolic generalizations

(such as the mathematical formalism of scientific laws); metaphysical beliefs (for instance, the

scholastic commitment to the existence of essential natures); values (such as those favouring

certain theoretical virtues, like simplicity); and exemplars (standard problem solving algorithms or

techniques). Scientific theories falling under the rubric of different paradigms are incommensurable

with one another – a metaphor derived from the origins of the term in the Greek geometrical

concept of having ‘no common measure’. If two theories are incommensurable with one another,

they are not incomparable per se, but they are not comparable in way that would allow one, for

example, to judge that one is true and the other false, or to determine that one is closer to the truth,

relatively speaking. This incommensurability may take the form of a difference in methods or

standards operative in science, differences in perception on the part of scientists whose

observations are differently “theory laden”, and most importantly for Kuhn, a difference in the very

meanings of our words. This semantic incommensurability, which he later analyzed in terms of the

failure of meaning preserving translation (Kuhn 1983), problematizes assessments of truth across

paradigms.

Kuhn’s theory of meaning is a species of meaning holism, or meaning contextualism: it

suggests that concepts are learned in groups, such as those constituting the sets of interconnected

beliefs composing paradigms. As a result, when some of these concepts change, the meanings of

terms throughout the network are invariably altered. Thus, the term ‘mass’ as used in classical

physics simply does not have the same meaning as the term ‘mass’ as used in relativistic physics,

and to suggest that one theory’s characterization of mass is closer to the truth is importantly

confused – it is to equivocate with respect to two very different concepts which cannot be

understood except from within the paradigms in which they occur. Indeed, this holism or

contextualism is so pronounced that Kuhn maintained that there is strong sense in which, after a

scientific revolution, scientists live in a different world. In the latter stages of his career Kuhn gave a

neo-‐Kantian gloss to this notoriously cryptic remark. One may think of different paradigms as

different lenses one must employ so as to engage in and indeed, create the reality of scientific

phenomena. Perhaps not surprisingly, this is a challenging idea to articulate and defend.

1 For just a few of the many detailed studies of these topics, see Horwich 1993, Hoyningen-‐Huene 1993, Sankey 1994, and Bird 2000.


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The pursuit of truth plays an important role, on this picture, during normal science. Within

the scope of a given paradigm, scientists solve problems and generate facts that may be described

in terms of truth. But across paradigms, such talk becomes incoherent. One cannot judge one

scientific theory to be closer to the truth than its predecessor if the very comparison is rendered

ineffectual by semantic incommensurability. And if one takes the idea of world change seriously,

the problem is compounded, for there is no paradigm-‐transcendent, God’s-‐eye point of view from

which to judge. There are only paradigmatic judgements; empirical reality is in part structured by

our paradigms. One might adopt a coherence theory of truth with respect to the intra-‐paradigmatic

context, since knowledge generated within a paradigm should cohere with it. This will not suffice to

allow for anything like scientific progress across paradigms, however, in the way one might hope

given a correspondence theory of truth. It is for this reason that those moved by historicist

approaches to scientific knowledge are not generally interested in the notion of truth. It is of limited

applicability, and entirely inapplicable in the case of correspondence truth. Those inspired by this

approach to engage primarily with descriptive features of scientific practice have also often found

truth to be an unhelpful or irrelevant concept.

2.2 The sociology of scientific knowledge

Among other innovations, the historical turn in the philosophy of science turned a spotlight

on the social context of the sciences. Descriptions of actual scientific practice revealed that complex

social interactions are intimately connected to the generation of scientific knowledge – from the

training of students by mentors, to the collaborative and competitive dynamics of the hierarchies of

public and private institutions in which scientific work is done, to the role of economic, political,

and other factors driving research by funding and other means, and so on. It was perhaps

inevitable, then, that in the wake of the historical turn some should turn to sociology as a means of

understanding the sciences. The sociology of scientific knowledge (SSK) investigates the social

contexts of the sciences, and in this by itself, it is philosophically neutral with respect to truth. Just

as those who are primarily interested in descriptive features of scientific practice might find the

notion of truth surplus to analytic requirements, those primarily interested in social aspects might

do likewise. In practice, however, most accounts of science inspired by SSK have significant

philosophical consequences. Many suggest that once one appreciates the role that social factors

play in generating scientific knowledge, a philosophical commitment to some form of social

constructivism is inevitable, and this once again problematizes the notion of correspondence truth.


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The term ‘social construction’ is used somewhat differently by different authors, but let us

proceed here with a general understanding of it, according to which it applies to any process

wherein what counts as scientific fact (that is, a claim having the status of scientific knowledge) has

been shaped and determined in substantive ways by social factors, and in which different social

factors (likely) would have produced facts that are inconsistent with those that were in fact

produced. The substantive influences of the social on the scientific are of course numerous

(consider, for example, the directions and methodologies of research permitted, encouraged, and

funded), but this does not by itself establish the counterfactual dimension of the idea of social

construction – the notion that had such influences been otherwise, one would have ended up with

facts that are inconsistent with those currently accepted. In order to motivate the counterfactual,

scholars in this vein have typically engaged in case studies of scientific work which aim to show

how contingent decisions in the workplace are both determined by social factors and could have

gone otherwise, resulting in different and potentially conflicting facts. Additionally, some have

offered more global reasons for thinking that such contingency is inevitable. Chief among the

proponents of the latter approach are supporters of the so-‐called “Strong Program” in SSK (also

known as the “Edinburgh School”).2

Two of the central tenets of the Strong Program are particularly interesting in connection

with the notion of truth. The first is the idea of symmetry, which suggests that in the scientific

domain inter alia, beliefs that are taken to be true are on a par with those taken to be false in that

both have the same causes, and thus should be given symmetrical explanations. This stands at odds

with the not uncommon, asymmetrical practice of explaining the generation of true beliefs in terms

of scientific investigation successfully latching on to some facet of a mind-‐independent world, while

explaining false beliefs in terms of something going wrong, whether it be instrument malfunction,

human error, corruption, or what have you. Putting all scientific belief on a par with respect to their

causes opens the door to a substantively social account of both truth and falsehood. A second tenet

of interest is the idea of reflexivity, which suggests that the claims of SSK are no less subject to

sociological analysis (including the symmetry principle) than any putatively factual claims. This

entails a wide-‐ranging commitment to relativism: truth and falsehood (even with respect to SSK)

are defined only in the context of a social community, and have no community-‐transcendent

2 For a mature statement of the Strong Program, see Barnes, Bloor & Henry 1996. For a sampling of different approaches to social constructivism, see Knorr-‐Cetina 1981, Pickering 1984, Shapin & Schaffer 1985, Latour & Woolgar 1986, and Collins & Pinch 1993.


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meaning. As with many relativist positions, there is ongoing debate as to whether this feature of the

view renders it self-‐undermining.

Later incarnations of the Strong Program adopt a theory of language acquisition, meaning

finitism, which also has profound implications for truth. Finitism can be viewed as an elaboration of

the later work of Kuhn, and especially as deriving from the philosophy of the later Wittgenstein.

Kuhn emphasized the idea that one learns the meanings of concepts by mastering the use of

exemplars that incorporate them, and this point can be extended to training, education, and

acculturation more broadly. The ensuing claim of finitism is that meanings are social institutions –

the meaning of a term is simply the concatenation of ways in which it can be used successfully in

communication within a linguistic community. This relegation of meaning to social facts can be

exploited so as to derive a forceful case for the idea that such terms need have no fixed or

determinate meanings at all. For on this view, the meaning of a term is constituted by the social

acceptance of its use, and this is something that can change subject to social negotiation, reflecting

collective decisions about how to go on using language, which may themselves not be universally

accepted. This once again appears to favour coherence as an analysis of truth regarding

propositions entertained within a scientific community. Whether finitist observations regarding

language acquisition successfully entail the associated view of meaning, however, is certainly

contestable.

2.3 Feminist critiques of science

Just as the historical turn in the philosophy of science suggested and facilitated the

emergence of SSK and the development of a number of forms of social constructivism, these latter

positions facilitated the development of feminist critiques of science, often in conversation with

them. There is significant overlap between SSK and feminist approaches in the acknowledgement of

the role of social factors as determinants of scientific fact, but feminist scholars have extended this

analysis in more specific ways, reflecting their more specific motivations. Another striking

difference is the near universality with which feminist approaches are normative, offering

corrective prescriptions for understanding concepts such as objectivity and knowledge (not to

mention proposals for reforming scientific practice itself) which, as we shall see momentarily, have

implications for how one conceives of truth.

Several prominent positions have emerged in this literature, and it will be useful to mention

them in passing. Feminist empiricism emphasizes the possibility of warranted scientific belief in a


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communal setting, but crucially, only where biases which enter into research – stemming from

gender, ethnicity, socio-‐economic or political status, and so on – are transparent and appropriately

considered. Standpoint theory explores the contention that differences in gender, ethnicity, socio-‐

economic and political status, etc. define perspectives to which knowledge is inextricably indexed.

Feminist postmodernism rejects traditional conceptions of universal or absolute objectivity or

truth.3 Taken together, these positions offer a number of considerations which might push one in

the direction of one theory of truth or another, or indeed, towards a rejection of any substantive

theory at all. Foremost among these are considerations of objectivity and perspective. Let us

examine them together, as they are interestingly connected.

The term ‘objective’, when used traditionally in connection with knowledge, has a number

of stereotypical connotations. Most important in this context are connotations of disinterest

(detachment, lack of bias), and of universality (independence of any particular angle of approach or

perspective). Knowledge of this sort arguably comprises propositions that are candidates for

describing a mind-‐independent world, and thus, is consistent with a correspondence theory of

truth. There is near consensus in feminist critiques of science that objectivity in the sense of

disinterest is regularly violated in science. Case studies are adduced to demonstrate how the

presence of, for instance, androcentric bias exemplified by a community of scientists can lead to the

establishment of one scientific fact at the expense of another, mutually inconsistent possibility (for

example, see Longino 1990 for detailed accounts of two cases: one concerning explanations of the

evolution of modern human biological characteristics in paleoanthropology; and another

concerning the influence of hormones on biological characteristics and behaviour in

neuroendocrinology). Many also reject the idea of objectivity in the sense of universality or

perspective-‐independence, and as I will suggest, it is this latter thesis that is required in order to

problematize the notion of correspondence truth.

Why is the presence of bias in scientific work not by itself sufficient to rule out

correspondence? There are two reasons for this. One is that the presence of bias may not be, in a

given case, epistemically significant. That is to say, if regardless of one’s bias one would have

assessed the evidence for a given hypotheses in the same way, one might thereby end up with true

beliefs concerning that hypothesis in the correspondence sense quite independently of one’s bias.

Of course, most feminist case studies are not of this sort – they are cases in which bias does make a

difference. A second reason that the presence of bias (taken by itself) is consistent with the idea of

3 For a sample of a number of influential versions of these views, see Keller 1985, Harding 1986, Haraway 1988, Longino 1990, Alcoff & Potter 1993, and Nelson & Nelson 1996.


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correspondence truth, is that if the institutional infrastructure of science were arranged in such a

way as to make epistemically significant bias transparent, then it should be possible in principle to

expose such bias and correct for it where necessary. It is for this reason that many feminist

philosophers of science advocate for institutional structures that would expose sources of bias.

Consider, for example, the idea of effective peer review, where “peers” are drawn from across the

space of possible biases exemplified by human agents. The contention that in many and perhaps

most domains, the sciences do not yet instantiate such structures, is one motivation for the

normative character of most feminist critiques.

If epistemically significant bias is a fact of the matter about much contemporary science,

then the prospect of scientific knowledge of a mind-‐independent world is thereby diminished in

practice if not in principle. A more in-‐principle concern emerges from the idea of perspectives. For

just as the Strong Program in SSK embraces a thoroughgoing relativism, where truth is defined only

within the confines of a context and not universally, some standpoint theory and certainly all

postmodernism is likewise dismissive of the idea of standpoint-‐ or perspective-‐independent truth.

It is important to note here, however, that some would reject this implication. Some standpoint

theorists, reflecting a Marxist inspiration, claim that certain perspectives are epistemically

privileged over others – typically, subjugated perspectives are privileged over dominant ones as

having deeper insight into the subject matter, in just the way that the proletariat might have deeper

knowledge of human potential than the superficial knowledge possessed by those in positions of

power. In the absence of such epistemic privilege, however, one is left with an irreducibly fractured

picture of warranted scientific belief, where (at best) coherence within perspectives, not

correspondence of beliefs from across perspectives, might serve as an analysis of truth.

3. Truth as an Aim of Science

3.1 The ideal end of inquiry

Having canvassed some reasons for dismissing the relevance of correspondence

conceptions of truth in the context of the sciences (in some cases, in favour of a notion of

coherence), or for dispensing with concerns about truth altogether, let us turn now to views in

which truth is offered explicitly as a goal of scientific investigation. One of the most influential

themes to emerge in the philosophy of science in this regard represents scientific inquiry as

converging, ultimately, on the truth. The idea of convergence has two features of particular


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relevance here. One is that convergence is something that can be realized by a process – in this case,

the development of scientific knowledge – quite independently of whether the goal itself is ever

realized. (Consider the analogy of a mathematical limit that can be approached but never quite

realized, accept at infinity.) Another feature of interest here is the broad compatibility of the notion

of convergence with different views of science. Some scientific realists, for example, whom we will

consider in section 4, hold that scientific knowledge is converging on truths in the correspondence

sense. But one need not be a realist of this or any other sort to think that truth is the ultimate aim of

science.

An important case in point of non-‐realist endorsement of convergence is associated with the

pragmatist tradition in philosophy. The terminology can easily mislead here, since some self-‐

avowed pragmatists also refer to themselves as realists, but as we shall see, their realism is

generally not what goes by the name ‘scientific realism’ more specifically. One way of generating

the distinction, conveniently for present purposes, is to pay attention to the theories of truth

typically endorsed by these camps. While scientific realists generally opt for some version of the

correspondence theory – or if they dislike classical accounts of truth, some version of truth-‐maker

theory – pragmatists generally do not. (This is a traditional characterization of pragmatism; for a

more nuanced treatment, see Misak in this volume.) In order to appreciate the pragmatist’s

conception of convergence, let us digress momentarily to consider her connected notions of

meaning, and truth.4

As is the case in any grand philosophical movement, not all participants share precisely the

same view, but one tenet shared by many if not all pragmatists is a commitment to a criterion of

meaning, whereby the content of a proposition is given, as C. S. Peirce put it in his essay ‘How to

Make Our Ideas Clear’, by clarifying its ‘practical consequences’. Such consequences are to be

understood in terms of human experience; that is, as having implications for actual or possible

empirical observations. In the context of the sciences, this concerns everything from successful

prediction, retrodiction, and communication, to heuristic use and problem solving, where

theoretical claims are employed as a basis for action. In the work of William James in particular, this

analysis of meaning was parlayed into a theory of truth, according to which positive utility of the

sort indicated by useful practical consequences is the marker of truth. Given the fallible nature of

scientific knowledge, however, the application of this concept is conceived of by many pragmatists

as something of an ideal: truth is whatever it is that will be agreed upon in scientific investigation in

4 Here I will focus on some general pragmatist principles drawn primarily from James 1979/1907 and Peirce 1998/1992, though readily recognizable in the work of many who have identified with pragmatism since.


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the ideal limit of inquiry. For both Peirce and James, the truth in this sense exhausts our conception

of reality, which is made by us, not mind-‐independent. Peirce in particular held that through a

process analogous to evolution, scientific methods will converge on a particular body of knowledge.

In this way, truth may be conceived as the ultimate aim of science.

The evolutionary analogy here is an evocative one, but its appropriateness in the context of

scientific knowledge may be questioned in a number of ways, including some we have already

considered. If strongly historicist readings of scientific knowledge are compelling, for example, then

the very idea of convergence is problematic, since in this case it is difficult to understand what it

could mean for scientific theories across different periods of history to be moving in any particular

direction. Indeed, Kuhn himself was attracted to an evolutionary picture of the development of

scientific knowledge, but of a rather different sort. On our modern understanding of the analogue –

evolution by natural selection – there is no sense in which the adaptations of organisms are

“moving” in the direction of anything resembling a definitive ideal. Adaptations in the biological

case are more or less optimal only relative to particular conditions of existence represented by

particular ecological settings, and the same sort of thing (mutatis mutandis) might be thought true

of knowledge in historical settings. It is for this reason that many regard the evolutionary analogy

as properly suggesting only a notion of progress from a particular state of knowledge, as opposed to

progress towards an ideal, and without the latter, there can be no convergence. Similar appraisals

can be generated from the point of view of some social constructivist and feminist positions, and

these are contested, as we shall see, by some varieties of realism, which like pragmatism subscribe

to the idea of convergence.

3.2 Constructive empiricism and one formulation of realism

The pragmatist notion of truth in the ideal limit of inquiry is an example of one manner of

thinking about truth as an aim of science. I have described this manner above in terms of

conceptions of the ultimate aim of scientific investigation. One might think of truth as a goal,

however, in rather different terms, as a proximate aim. That is to say, one might think that the

sciences aim at the truth in the present, not merely as an imagined outcome in a limit. Indeed, it is

possible to hold that truth is both a proximate and an ultimate aim of science in precisely these

senses – that by aiming at truth in the present, one might thereby realize it in the limit of inquiry,

whether this limit is held to be an idealization (as suggested by Peirce), or something one might

think is achievable in a finite time, or even now with respect to some scientific facts, as many (if not


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all) realists contend. This combination of proximate and ultimate aims would seem to be consistent

with any position that takes scientific knowledge to be converging on the truth, in some way, shape,

or form. Having considered one version of the idea that science aims at truth in the limit, let us turn

to the idea that it aims at truth in the here and now.

Bas van Fraassen (1980) has been influential in suggesting that different views of the nature

of scientific knowledge can be described in terms of how they view the proximate aim of science.

This, I submit, is a tricky business, for it is unclear why any view of scientific knowledge should take

it to have any one particular or primary aim, given the many candidates that seem to be

transparently evident in scientific practice. Based on the activities of scientists, one might plausibly

contend that the sciences aim to describe, to predict, to explain, and much more besides. Given this

plethora of aims, a question arises as to what philosophical argument could establish the primacy of

any one in particular. One possibility here would be to argue that some particular, over-‐arching,

epistemic aim makes good sense of scientific practice and its various other aims, by accounting for

the latter aims as subsidiary to the former. Pronouncements regarding “the (proximate) aim of

science” issuing from philosophical accounts of scientific knowledge generally do not engage in

such argument, however, and for this reason, any claim of this sort must be viewed as harbouring a

significant promissory note.

Van Fraassen offers a characterization of scientific knowledge in terms of aims on behalf of

two positions: his own view, which he calls ‘constructive empiricism’; and the view with which he

contrasts it, scientific realism. The constructive empiricist holds that the aim of science is empirical

adequacy, where this is defined in the following way: ‘a theory is empirically adequate exactly if

what it says about the observable things and events in the world, is true’ (1980, p. 12).5 In contrast,

realism is described as the view according to which the aim of science is truth simpliciter – not

merely regarding scientific claims about observable things and events, but also regarding claims

about unobservable things and events. In both cases, truth may be understood in a correspondence

sense, and the distinction between the observable and the unobservable is drawn in terms of

human sensory capabilities. Whatever is detectable by the unaided senses (such as planets, alpacas,

and metals) is observable, and whatever is not so detectable (such as dark matter, genes, and

5 This definition suffices for present purposes, but it is worth noting that van Fraassen goes on to define empirical adequacy again in more technical terms: a theory is empirically adequate if the observable content of scientific investigation – ‘the structures which can be described in experimental and measurement reports’ (1980, p. 64) – are isomorphic to empirical substructures of some model or models of the theory, where a model is understood to be any structure of which the axioms and theorems associated with the theory are true. The relevant empirical substructures can then be taken to represent observable things and events.


14

neutrons) is unobservable. While this particular opposition regarding the putative aim of science

has attracted significant attention, one could no doubt imagine other possible epistemological

stances with respect to scientific knowledge, each defined by a different proposal for the principal

aim of scientific investigation.

There is arguably good reason, however, to be dissatisfied with this strategy for defining

epistemological positions such as constructive empiricism and scientific realism. To define an

epistemological position purely aspirationally – that is, in terms of aims – may strike one as too

weak. For so defined, these positions are consistent with never actually achieving the relevant aim;

indeed, they are consistent with the impossibility of achieving the relevant aim. Defined

aspirationally, constructive empiricism is consistent with the belief that no scientific theory is

empirically adequate, and with the belief that no theory will ever or could ever be empirically

adequate. The same moral would seem to apply to realism, in connection with a more

comprehensive truth of theories, covering both the observable and the unobservable. This

separation of views concerning what science aims to do from those concerning what it actually

achieves, or is capable of achieving, is perfectly consistent insofar as one is interested in aims alone.

But from the point of view of epistemology, it is too weak. Many realists, for example, believe not

only that the sciences aspire to truth, but that under certain conditions, they achieve this aim, in a

manner to be specified. Let us move on now, to consider philosophical approaches to scientific

knowledge that explicitly adopt an achievement view of truth.

4. Truth as an Achievement of Science

4.1 The many forms of realism

There are many analyses of scientific knowledge that are or could be, if interpreted in a

favourable manner, consistent with the idea that scientific theories are true, to some extent or

other. This last qualification, ‘to some extent or other’, introduces a complication which I have thus

far ignored, but must now address. Those who believe that the sciences yield truths are often very

careful about how they describe this commitment to truth. Some scientific claims (for example,

certain claims about what sorts of things exist), they might say, are likely true simpliciter, but others

(such as descriptions of laws of nature, or theories taken as wholes) are often merely approximately

true – that is, close to the truth, in some sense to be explicated. Convergentists in this camp then

commonly hold that scientific theories are becoming increasingly approximately true over time,


15

with the development of science. I will return to the idea of approximate truth in section 5, but let it

suffice here to say that when I describe views that take truth to be an achievement of the sciences, I

am including those which subscribe to the of idea of approximate truth as an appropriate surrogate

for truth simpliciter, as and where appropriate.

A further qualification is in order here, concerning the breadth of positions that might, on a

favourable interpretation, qualify as admitting scientific truths. Many so-‐called antirealist positions

in the philosophy of science are consistent with scientific truth, but only regarding a very specific

domain: the observable. Instrumentalism, for example, is the view that scientific theories are simply

instruments for predicting observable phenomena, or for systematizing observation reports. On a

traditional reading, this view also holds that claims pertaining to unobservable things, by

themselves, have no meaning at all – they are merely instruments, not candidates for truth or

falsity. Less traditionally, positions are sometimes described as instrumentalist if they admit

epistemic access only to truths about observables; claims about unobservables here may be true or

false, but the relevant truth value cannot be known. In either case, it is open to an instrumentalist to

believe that the sciences yield truths about observables in the correspondence sense. Others, such

as some logical empiricists, might agree, but only insofar as truth is understood in terms of

coherence, in accordance with some or other form of neo-‐Kantianism. Others, such as Kuhn, might

extend the remit of the neo-‐Kantian-‐coherence-‐type approach to truth to the unobservable, but

only within periods of normal science. As should be clear, the possible combinations of restriction

on the domain of truth, and theory of truth applicable, are many!6

The most unequivocal commitment to truth talk in connection with the sciences, however,

is exemplified by versions of scientific realism. Most realists suggest, either explicitly or implicitly,

that our best scientific theories are true or approximately true in some appropriate sense of

correspondence with a mind-‐independent world.7 Understood this way, scientific realism is

the view that scientific theories correctly describe both observable and unobservable features of

the world. The main consideration offered in support of realism is an old idea, resonant with

common sense, to the effect that the very empirical success of science – in prediction and

6 For a formative influence on instrumentalism, see Duhem 1954/1906. For discussion of the neo-‐Kantian reading of logical empiricism, see Richardson 1998 and Friedman 1999, and for a reading more compatible with realism, see Psillos forthcoming. The neo-‐Kantian theme is developed differently under the label ‘internal realism’ in Putnam 1981. For a consideration of fictionalism, which holds that things in the world are and behave is as if our best scientific theories are true (thus admitting truths about observables), see Vaihinger 1923/1911 and Fine 1993. 7 There are exceptions, however. For arguments in favour of separating realism from the correspondence theory of truth, see Ellis 1988, Leeds 2007, and Devitt 2010 (especially chapters 2 and 4). I will return to this idea in another form in section 5.


16

manipulation of the natural world, not to mention technological applications – indicates that its

theories are true. In recent times this idea is commonly referred to as the ‘miracle argument’ (or

‘no-‐miracles argument’), after Hilary Putnam’s (1975, p. 73) contention that realism ‘is the only

philosophy that doesn’t make the success of science a miracle’. In other words, it would be

miraculous if the sciences were as empirically successful as they are, and yet their theories were

untrue, thus suggesting the greater credibility of an explanation of success that appeals to truth. As

we shall see momentarily, however, the miracle argument is highly contested.

As it happens, there are many varieties of scientific realism, some developed with the

intention of responding to forms of antirealist scepticism such as that concerning the miracle

argument. The most general form of realism subscribes to the formula I have already presented: a

general endorsement of the truth of our best scientific theories. Of the variations on this formula to

emerge, two in particular have come to prominence in recent philosophy of science, both of which

offer a more specific prescription for realist commitment. Entity realism is the view that under

conditions in which one has significant causal knowledge of a putative (unobservable) entity,

allowing one (ex hypothesi) to manipulate it and use it to intervene in other phenomena, one has

good reason to think it exists, and consequently, that claims about the existence of such entities are

true. The negative implication of this commitment is that the theories that describe these entities

need not be true, and this raises a question about whether an antirealism about theories is

ultimately compatible with a realism about the entities they describe. This view also appears to

entail that one may continue to believe in the existence of an entity despite radical changes in one’s

(theoretical) understanding of what that entity is like. This in particular might seem problematic

from a historicist point of view, or indeed, from any point of view that takes accurate description to

be an important component of successful reference to an entity.

A second more specific version of realism is structural realism, which holds that insofar as

scientific theories offer true descriptions, they do not tell us about the natures of things like

unobservable entities. Instead, they correctly describe the structure of the unobservable realm.

There are two main sorts of structural realist positions: those that take the distinction between

structure and nature to be an epistemic distinction; and those that take it to be an ontological

distinction. The former suggest that knowledge of the entities that participate in the structural

relations described by theories (for example, by mathematical laws) is simply beyond our grasp,

but that theories furnish a kind of structural knowledge nonetheless. The latter suggest that

structural knowledge is the most a realist can hope for, because there are in fact no entities that

stand in those relations, or that if there are such entities, they are in some sense emergent from or


17

dependent on the structures in which they seem to appear. Like entity realism, structural realism

faces interesting challenges. One might wonder, for example, about how clear the distinction

between structure and nature is, or whether this distinction is tenable in connection with the

concrete systems of things investigated by the sciences. The ontological version specifically faces

the challenge of making the relevant ideas of emergence and dependence of entities intelligible.8

4.2 Scepticism about realism

Entity realism and structural realism each face challenges aimed at the coherence of their

specific formulations of realist commitment. Additionally, it is important to note that all the reasons

we encountered earlier for being suspicious of the notion of correspondence truth, in connection

with different views regarding the nature of scientific knowledge, are also ultimately challenges to

scientific realism as it is usually conceived. Often, in the background of these worries, are more

general sceptical concerns about scientific knowledge that any realism must face if it is to be

defensible. Indeed, the advent of both entity realism and structural realism was intended, in part, to

offer responses to some of these more general concerns. I will not here consider whether or to what

extent they are successful in this regard, but given the importance of these concerns to motivating

(sometimes explicitly but often implicitly) a number of the antirealist positions we encountered

earlier, let us consider them briefly. This more general antirealist scepticism stems from three

notable issues: the ubiquitous use in science of a form of reasoning called inference to the best

explanation; the so-‐called underdetermination of theories by data; and discontinuities in scientific

theories over time.

Scientific inferences are generally inductive. One is rarely if ever in a position to generate

scientific conclusions, laws, theories, and so on, by means of arguments that are deductively valid.

Instead, one marshals evidence by means of observation and experiment, and reasons on the basis

of this and other commitments to conclusions that are, ideally, inductively strong. In the sciences, a

particular form of inductive inference is prevalent, viz. inference to the best explanation, according

to which one infers hypotheses that, if true, would provide the best explanation for whatever it is

that one is attempting to explain. Natural though this pattern of inference may be, antirealists have

8 For a defence of scientific realism, see Psillos 1999. For a discussion of novel predictions, often invoked in characterizing what it might mean for something to be one of our best theories, see Leplin 1997. Cartwright 1983 and Hacking 1983 are definitional texts for entity realism, as are Worrall 1989, French 1998, and Ladyman & Ross 2007 for structural realism. For a discussion of the relationships between scientific realism, entity realism, and structural realism, see Chakravartty 2007.


18

been quick to point out two potential difficulties with it in connection with truth. First, in order that

one infer the truth, one must have the capacity to rank rival hypotheses reliably with respect to

their likelihood of being true. But what assurance is there that the sorts of criteria typically

employed in the sciences for purposes of ranking – the simplicity of a hypothesis, its consistency

with other hypotheses one may like, its heuristic value, and so on – are indicative of truth? And

even if one were to grant that the criteria for choice employed in scientific practice are truth-‐

tracking, in order for inference to the best explanation to result in true belief, it is imperative that

the true hypothesis be among those one is considering. But this, arguably, is not generally

something one can know in advance.9

Moving on now to our second sceptical concern, the idea of the underdetermination of theory

by data, derived from the work of Pierre Duhem, runs this way.10 Scientific hypotheses do not yield

predictions all by themselves. In order to derive predictions, they must be conjoined with background

theories, other theories, theories about instruments and measurements, and so on. Now, if observation

and experiment result in data that do not agree with one’s predictions, what part of one’s scientific

belief set should one adjust accordingly? Naively, one might think that the hypothesis under test

should now be viewed suspiciously, but Duhem points out that given all of the things one must assume

in order to derive the faulty prediction in the first place, it is not so obvious which part of this

apparatus deserves suspicion. Different adjustments to one’s belief set – different overall conjunctions

of hypotheses and theories – will be consistent with the data. Therefore, there is always more than one

overall set of beliefs that is consistent with the data. In more contemporary discussions,

underdetermination is usually presented slightly differently, in terms of the idea that every scientific

theory has empirically equivalent rivals: ones that agree with respect to the observable, but differ

elsewhere. This then serves as the basis for a sceptical argument regarding the truth of any particular

rival chosen for belief. It is precisely this sort of scepticism that underwrites the worries about

correspondence truth commonly found in SSK and feminist critiques of science.

Finally, let us turn to an argument that is often simply referred to as the ‘pessimistic

induction’, or the ‘pessimistic meta-‐induction’. The history of the sciences is replete with

discontinuities in the knowledge they ostensibly provide. Over time, older theories recede into the

past as newer theories are proposed and accepted, resulting in changes in belief with respect to the

9 For a thorough exploration of inference to the best explanation, see Lipton 2004, and for an influential critique of it, see van Fraassen 1989, chapter 6. 10 The idea of underdetermination is commonly traced to Duhem 1954/1906, chapter 6, and many see affinities here with the later “confirmational holism” of W. V. O. Quine (1953). For this reason, it is sometimes called the ‘Duhem-‐Quine thesis’.


19

entities, their properties and relations, and laws described by these theories. Thus, from the point

of view of any given moment in time, most past theories must be considered false, strictly speaking.

By induction, then, is it not likely that most present-‐day theories are also false? The ways in which

they will, in future, be revealed as false may not yet be clear to us, but the inductive challenge

remains. Given a knowledge of the history of theorizing in any particular domain of scientific

investigation, realism may thus appear a rather too optimistic position regarding scientific

knowledge. This general sceptical worry can be posed in a number of different ways, focusing on

the falsity of past theories, unsuccessful reference on the part of their central terms, and in other

ways besides.11

Worries about inference to the best explanation, the underdetermination of theory by data,

and the pessimistic induction have been highly influential in the philosophy of science. It would be

irresponsible not to mention, however, that realists of various stripes have responded to these

concerns in a number of ways, and the ensuing debates are very much alive. A thorough canvassing

of the details of these debates lies far beyond the scope of this essay – indeed, these details

comprise a large proportion of the field itself. I hope, however, that the ways in which the notion of

truth bears on the sciences is now substantially clearer than when we began. My aims in this regard

now largely fulfilled, let us turn in the next and final section to a few important considerations

involving truth to emerge in areas of very recent interest in the philosophy of science.

5. Truth and scientific models

5.1 Abstraction and idealization

One of the most important developments in the philosophy of science over the past two

decades has been an increasing awareness and study of the role of scientific models in discussions

of scientific knowledge. In keeping with a general movement towards closer attention to scientific

practice in the wake of the historical turn, a traditional emphasis on knowledge encapsulated by

scientific theories has been supplemented (and perhaps, in some authors’ estimations, replaced) by

an emphasis on the ways in which models associated with these theories are used to represent

target systems in the world. One reason for this, no doubt, is that ‘scientific theory’ is a somewhat

loosely defined concept – its referents vary significantly depending on the context of its use. One

11 Canonical formulations of the pessimistic induction are most often drawn from Laudan 1981. For a related and more recent version of history-‐induced scepticism, see Stanford 2006.


20

and the same theory may be identified in some cases with a set of equations, and in other cases with

various models applied to different classes of phenomena putatively described by those equations,

but in different ways. These different adaptations of mathematical descriptions to fit particular

sorts of cases – sometimes even in ways that are mutually inconsistent – suggests that in many

situations, it is the models themselves that are the primary representational tools of scientific

description. Thus, a spotlight is turned onto the relationship between modelling and truth.

The term ‘scientific model’ covers many things here. It includes: abstract entities, such as

theoretical models about which scientists may have some shared conception; concrete objects, such

as graphs, diagrams, other illustrations, and three-‐dimensional physical representations, such as

scale models; and processes, such as computer simulations. Though the forms of these

representations are many, the question of how they can be thought to represent their targets

veridically, if at all, has become a central topic of debate, not least because, as it happens, scientific

models are often constructed so as to deviate from the truth. There are two primary ways in which

this occurs, and I will call these practices abstraction and idealization. Although these are terms of

art, used in slightly different ways by a growing number of philosophers, there is something of a

consensus regarding the basic distinction. For purposes of illustration, I will sketch a representative

version of this distinction below.12

‘Abstraction’ and ‘idealization’ can be thought of as labelling processes – ones by means of

which models are constructed – as well as the resultant models themselves. Thus, an abstract

model is the result of a process of abstraction, a process in which only some of the potentially many

factors that are relevant to the nature or behaviour of something in the world are represented in a

model of it. In the process of abstraction, other factors are ignored, often intentionally, in order to

allow for the construction of models that are mathematically or otherwise tractable; and often

relevant factors are unintentionally ignored, because their relevance is unknown. Consider, for

example, the model of a simple pendulum. Many simplifying assumptions are made in constructing

this model, such as the omission of frictional resistance due to the air in which the pendulum

swings. Such assumptions are commonly held to compromise the truth of models not only because

theoretically important aspects of their target systems in the world are left out, but also because, as

a result, the predictions of these models differ from that which one finds in reality. One might argue

that in both of these ways, abstraction introduces falsehood into practices of scientific

12 For influential discussions in this area, see McMullin 1985, Cartwright 1989 (chapter 5), and Suppe 1989 (pp. 82-‐83, 94-‐99). For a comprehensive treatment, see Jones 2005. My take on the distinction here is abridged from Chakravartty 2010a, which considers the implications for truth in some detail.


21

representation. By the same token, however, the notion of abstraction suggests one way of making

sense of the idea that one representation can be more approximately true than another: by

incorporating a greater number of factors that are causally (or otherwise) relevant to their natures

or behaviours.

Similarly, an idealized model is the result of a process of idealization, a process in which at

least one of the features of the target system incorporated into the model is represented in a

distorted or simplified manner. This process differs from abstraction in that one is not excluding

factors, but rather incorporating them in such a manner as to represent them in ways they are not.

(In order to sharpen the distinction between abstraction and idealization further, I view the latter

in terms of representing things in ways they could not be, given the laws of nature. This is

sometimes but not always true of abstract models: some abstract descriptions may be true of other

systems in the world in which the omitted factors happen not to be present, which is something

scientists often contrive in laboratory settings. In any case, given that abstraction and idealization

are not mutually exclusive processes, some models may be both abstract and idealized.) Idealized

models are, in a stronger sense than in the case of abstractions, false representations of things in

the world. It is an implicit assumption of classical physics, for example, that the masses of bodies

are concentrated at extensionless points at their centres of gravity, but this is something we clearly

know to be false, notwithstanding the predictive and explanatory efficacy of models in classical

physics. In such cases, understanding how one model can be more approximately true than another

is more complex than in the case of abstraction, turning on how “degrees” of distortion may be

conceived in particular cases.

5.2 Approximate truth and deflation

The notion of approximate truth is generally viewed as important to scientific realism,

versions of which, as we have seen, are commonly more interested to characterize scientific

knowledge in terms of truth than any other philosophical assessment of the sciences. The apparent

importance of approximate truth here is plain, given that even realists must acknowledge that

many if not all scientific theories contain falsehoods, and are thus, strictly speaking, false. The task

of reconciling the realist’s positive appraisal of scientific knowledge in terms of truth with such

obviously recalcitrant evidence of falsity provides strong motivation for thinking about how one

theory can be “better off” than another with respect to truth, even when both are false.


22

The concept of approximate truth, and others such as ‘verisimilitude’ and ‘truthlikeness’

(sometimes used synonymously with ‘approximate truth’ and in other cases not, reflecting the

intentions of different authors), have become subjects of detailed and technically striking work in

their own right. I will not consider these developments here (but another essay in this volume does;

see Oddie). Instead, my goal in this last section is to complete an examination of the implications of

the recent interest in scientific modelling for considerations of approximate truth, and for truth

more generally. For some advocates of the modelling conception of science hold that once one

appreciates how models are used to represent things in the world, all substantive concerns about

truth in this context are dissolved. These concerns arise in the face of two challenges: first, the

challenge of explicating the notion of correspondence truth; and second, the challenge of explicating

the notion of approximate truth. Given the difficulties inherent in both of these challenges, if it were

the case that paying attention to practices of scientific modelling could obviate the need to meet

them, this would be a significant result. Let us consider the prospects for doing so.

The most straightforward exposition of the idea that considerations of scientific modelling

dissolve substantive issues of truth for the realist is found in the work of Ronald Giere, on whose

view a scientific theory is constituted by ‘two elements: (1) a population of models, and (2) various

hypotheses linking those models with systems in the real world’ (1988, p. 85).13 Hypotheses assert

relationships of similarity between aspects of models and their target systems, and are true or false

depending on whether these relationships obtain. It is the fact that models are the tools by means of

which these epistemic commitments are expressed that dissolves concerns about truth, or so the

argument goes. On this approach, Giere contends, there is no question of attempting to forge any

sort of correspondence between linguistic entities and the world, and consequently, the challenge

to explicate the notion of correspondence truth does not even arise. All that is required are

assertions of similarity between models and the world, and for this a deflationary account of truth

will suffice.

Deflationism about truth holds that there is nothing metaphysically substantive (such as the

notion of correspondence) to the idea of truth (see Azzouni in this volume). One influential version

of the view suggests that the predicate ‘is true’ in ‘α is true’ is redundant; it adds nothing to the

meaning or the assertion of ‘α’. Thus, to say that it is true that a two-‐body Newtonian gravitational

model is similar in various ways to the system comprising the earth and moon, for example, is

13 Giere refines this portrait of scientific theories in subsequent work, but the refinements are immaterial for present purposes. For his most developed view of scientific knowledge borne of modelling, see Giere 2006, and for an appraisal of this sort of approach, see Chakravartty 2010b. For a longer discussion of modelling, correspondence, and approximate truth, see Chakravartty 2007, sections 7.4-‐7.5.


23

simply to say that these similarities obtain – the truth predicate is redundant. And once scientific

claims take the form of asserted model similarities, clarified in terms of respects and degrees of

similarity, the need for an overarching account of approximate truth is likewise superfluous, or so

one might argue.

The modelling approach facilitates many important insights into the nature of scientific

knowledge, but it does not, I suspect, make the issue of correspondence disappear for the realist.

Whether one prefers to think of correspondence in terms of a property shared by all truth-‐bearers,

or in terms of the existence of truth-‐makers for scientific claims, some form of correspondence is a

requirement of realism. As a quick demonstration of the insufficiency of asserted model similarities

in this context, consider the claim that the double-‐helical structure of Watson and Crick’s physical

model of the DNA molecule is similar to the double-‐helical structure of DNA molecules. Most

scientific realists would endorse this claim, but so too would most traditional instrumentalists. The

assertion of similarity here does not by itself distinguish the different ontological significance these

different parties attach to it. For the realist, the assertion of similarity is interpreted as truly

describing the properties of an unobservable entity, whereas for the instrumentalist, it is

interpreted as asserting something that is neither true nor false, but useful as a vehicle for the

derivation of observable predictions. It is only by admitting the relevance of considerations of

correspondence, in one form or another, that allows one to distinguish these interpretations.

Neither does the possibility of describing similarities between scientific models and their

target systems eliminate the yearning for an account of approximate truth. Though similarities of

this sort are the bread and butter of scientific representation, there are undoubtedly other

epistemic contexts, of a broader and grander sort, in which scientists and philosophers alike find

themselves, understandably, reflecting on the notion of truth. Stepping back from the minutiae of

particular representations to the world of scientific knowledge more broadly conceived, there are

contexts within which it is entirely appropriate to contend that relativistic physics is closer to the

truth than classical physics, or that the modern synthesis in evolutionary biology is closer to the

truth of the nature of organisms and their populations than biology before Darwin. It is precisely

this sense of progress that is celebrated by many realists, and in different ways by other

convergentists, and disputed by varieties of historicists and social constructivists. It is this sense of

truth that is the subject of so many of our most important and productive philosophical disputes

about the relationship of truth to the sciences.


24

Acknowledgments

For helpful comments on an earlier version of this essay, I am grateful to Agnes Bolinska and

Michael Glanzberg.

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